Researchers in Alberta are experimenting with artificial intelligence to measure the risks of prescription opioids amid the ongoing drug overdose crisis across Canada.
While doctors have a set protocol to identify patients at risk of opioid addiction, Dr. Dean Eurich said machine learning "could do a better job" of pinning down who is most susceptible.
"The model predict risks of hospitalization," said Gilani, who is the program manager of prescribing, analytics and the tracked prescription program at the college. The researchers looked at about three million opioid prescriptions a year from various medical professionals -- doctors, nurse practitioners, dentists -- to more than 600,000 patients in Alberta. Those who had cancer or were receiving palliative care were excluded.
He said the machine learning takes a different approach, building systematic models with a nuanced set of data, including various key factors, and finding the combinations predicting the best outcomes for a patient.
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